Intelligent real-time blood glucose monitoring system and method based on cloud big data is disclosed. The system includes an implantable dynamic glucose sensor, a smart phone, a blood glucose monitoring software application installed on the smart phone, a finger blood glucose meter, and a big data cloud server. By processing historical blood glucose measurement data of a user stored in the cloud, the monitoring system effectively corrects and influences signal differences produced by individual users so as to ensure the validity and accuracy of measurement signals during sensor operation.
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2. The intelligent real-time dynamic blood glucose monitoring system based on the cloud big data according to claim 1, wherein the personal information and the historical data stored in the cloud big data server of the user comprises user's name, gender, age, contact number, serial number and related information of the implantable dynamic glucose sensor, raw data Is of the implantable dynamic glucose sensor, signal-to-noise ratio SNR, blood glucose output value SG and measurement time and date Ts corresponding to the SG, a conversion coefficient CF and a related parameter between original data of the implantable dynamic glucose sensor and a blood glucose value, the blood glucose value BG measured by the finger blood glucose meter and measurement time and date Tb corresponding to the BG, electrochemical impedance data Z measured by the implantable dynamic glucose sensor and measurement time and date Tz corresponding to the Z.
This intelligent real-time dynamic blood glucose monitoring system, which uses cloud big data, includes an implantable dynamic glucose sensor, a smartphone running monitoring software, a finger blood glucose meter, and a big data cloud server to process historical data and correct sensor signals for individual users. The system specifically stores comprehensive personal and historical data in its cloud big data server. This stored information includes the user's name, gender, age, contact number, and details about their implantable dynamic glucose sensor (serial number, related information). It also records raw data (Is) from the sensor, its signal-to-noise ratio (SNR), the sensor's blood glucose output value (SG) with its timestamp (Ts), and conversion parameters (CF) relating raw sensor data to a blood glucose value. Furthermore, the server stores blood glucose values (BG) from the finger blood glucose meter with their timestamps (Tb), and electrochemical impedance data (Z) from the implantable sensor with its timestamp (Tz).
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October 8, 2018
March 26, 2024
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